Abstract. Coal-fired power plants influence climate via both the emission of
long-lived carbon dioxide (CO2) and short-lived ozone and aerosol
precursors. Using a climate model, we perform the first study of the spatial
and temporal pattern of radiative forcing specifically for coal plant
emissions. Without substantial pollution controls, we find that near-term
net global mean climate forcing is negative due to the well-known aerosol
masking of the effects of CO2. Imposition of pollution controls on
sulfur dioxide and nitrogen oxides leads to a rapid realization of the full
positive forcing from CO2, however. Long-term global mean forcing from
stable (constant) emissions is positive regardless of pollution controls.
Emissions from coal-fired power plants until ~1970, including roughly
1/3 of total anthropogenic CO2 emissions, likely contributed little net
global mean climate forcing during that period though they may have induce
weak Northern Hemisphere mid-latitude (NHml) cooling. After that time many areas imposed
pollution controls or switched to low-sulfur coal.
Hence forcing due to emissions from 1970 to 2000 and CO2 emitted
previously was strongly positive and contributed to rapid global and
especially NHml warming. Most recently, new construction in China and India
has increased rapidly with minimal application of pollution controls.
Continuation of this trend would add negative near-term global mean climate
forcing but severely degrade air quality. Conversely, following the Western
and Japanese pattern of imposing air quality pollution controls at a later
time could accelerate future warming rates, especially at NHmls. More broadly, our results
indicate that due to spatial and temporal inhomogenaities in forcing,
climate impacts of multi-pollutant emissions can vary strongly from region
to region and can include substantial effects on maximum rate-of-change,
neither of which are captured by commonly used global metrics. The method we
introduce here to estimate regional temperature responses may provide
additional insight.